Engineering Manager, Fraud & Compliance
Quick Summary
About Mercor Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models.
Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents.
Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices.
We're building the infrastructure that powers one of the world's largest expert networks and delivers expert data at unprecedented scale. We're looking for exceptional engineering leaders to help us protect the integrity of that ecosystem — building the fraud, risk, and compliance systems that make a global expert marketplace trustworthy at scale.
We value builders who have repeatedly chosen difficult problems, thrived in environments with high expectations, and can point to concrete examples where their leadership materially changed the trajectory of a team, product, or company.
We're still early.
Fraud is one of Mercor's most important business challenges. Every day, we process enormous volumes of applications, assessments, identity verifications, and work activity across a global talent network. Protecting that ecosystem requires sophisticated systems that can identify fraudulent behavior, evaluate risk, and make accurate decisions at scale — and the playbooks for doing it on an AI-native expert marketplace don't yet exist.
Fraud is an adversarial problem. The solutions that work today may not work six months from now. You'll lead engineering efforts focused on:
Responsibilities
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Lead and grow a high-performing team of engineers responsible for fraud detection, identity verification, abuse prevention, and platform integrity
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Define and execute Mercor's fraud and compliance engineering roadmap in partnership with product, operations, and company leadership
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Build systems that generate fraud signals, evaluate risk, make automated decisions, and continuously improve through human review and feedback loops
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Drive the development of AI-powered detection systems, including LLM-based decision engines, scoring models, and review workflows
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Establish rigorous evaluation frameworks to measure detection performance, confidence calibration, false positive/negative tradeoffs, and business impact
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Recruit exceptional engineers and raise the talent bar across the organization
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Partner closely with product, operations, and company leadership
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Drive engineering excellence, velocity, and operational rigor in an adversarial, fast-moving domain
Requirements
~1 min read5+ years of backend software engineering experience building and operating production systems at scale
3+ years of engineering management experience leading high-performing software engineering teams
Experience leading teams through periods of significant scale, ambiguity, or rapid change, with clear examples of the impact you've personally driven
2+ years delivering infrastructure for fraud, trust & safety, risk, identity, payments, abuse prevention, or other adversarial domains
2+ years working with machine learning, AI systems, decision engines, or risk-scoring platforms
What We Offer
~1 min readLocation & Eligibility
Listing Details
- Posted
- April 10, 2026
- First seen
- May 19, 2026
- Last seen
- September 26, 2026
Posting Health
- Days active
- 129
- Repost count
- 0
- Trust Level
- 39%
- Scored at
- September 26, 2026
Signal breakdown
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